LAKESHORELABS

AI ENGINEERING · SENIOR PODS · US / EU / SEA

We build AI systems that make it to production.

Agentic systems, document intelligence, and ML platforms, delivered by a 20+ person team where every engineer has 10+ years of experience. Working prototype in days. Production in weeks. Fixed prices, published below.

See offers and prices See shipped work
PROTOTYPE: DAYSPRODUCTION: WEEKSEVERY ENGINEER: 10+ YRSSUBCONTRACTORS: ZEROYOUR CODE: YOU OWN IT
/01

Fixed offers, published prices

Every engagement is phased with a go/no-go gate, so you never sign for more than the next deliverable. Typical US boutique proofs of concept run $25K to $75K and take a month or more. We price below that and move faster, with an all-senior team.

START HERE

Agentic Prototype Sprint

$15K fixed · 2 weeks

  • A working agent or retrieval system against your real data, not a slide deck
  • Live demo plus an architecture memo your team keeps
  • Go/no-go recommendation with an honest cost map to production
  • First working demo inside the first week

SHIP IT

Production Build

from $50K phased · 4 to 8 weeks

  • Discovery, build, pilot, production: a gate at every phase
  • Evaluation harness, observability, and cost-per-query dashboards included
  • Model agnostic: we pick what wins on your evals, not our partnerships
  • Full IP assignment: your code, your models, your data

SCALE

Dedicated Senior Pod

$25K/mo 2-3 seniors + lead

  • An embedded team in your repos, your tools, your standup
  • Monthly go/no-go: cancel at any gate, no lock-in
  • Comparable US pods run $40K+ per month
  • Timezone overlap guaranteed with your working day
/02

Shipped work

Global E-commerce Platform

AI customer service automation

LLM-based support automation for an e-commerce platform: intent classification, retrieval over policy and order data, CRM and ticketing integration.

70%Faster response time
95%Customer satisfaction
$2.5MAnnual cost savings
Read the case →

Leading Financial Services Provider

Intelligent document processing

Automated data extraction from complex financial documents: OCR, layout-aware models, and human review queues feeding downstream systems.

85%Faster processing
99.2%Accuracy rate
1M+Documents processed
Read the case →

Fortune 500 Manufacturing Company

Predictive maintenance platform

IoT-driven failure prediction for manufacturing equipment: streaming telemetry ingestion, time-series models, and operational dashboards across multiple facilities.

45%Reduction in downtime
$8MSaved annually
92%Prediction accuracy
Read the case →

National Retail Chain

Retail analytics and personalization

Real-time analytics and personalization for a national retail chain: behavioral event pipelines, segmentation, and recommendation surfaces across web and email.

35%Increase in conversion
28%Higher cart value
42%Better retention
Read the case →

Major F&B Group (SEA)

R&D research agent for F&B innovation

Research agent for a major F&B group synthesizing trend and product research from 100+ sources into briefs its innovation team acts on directly.

70%Faster time-to-insight
Read the case →

Cafe and Restaurant Chains (SEA)

Autonomous social media agents

Autonomous content agents for cafe and restaurant chains that draft, schedule, and post localized content across multiple regions and languages.

3.5xFollower engagement
15 hrs/weekManual work freed up
Read the case →

Regional Distributor

Sales augmentation agent

AI sales co-pilot for a distributor surfacing upsell and cross-sell opportunities directly inside the CRM.

12%Increase in order size
15%Shorter sales cycle
Read the case →

Health Insurance Provider

Benefits and claims assistant

Conversational assistant for health-insurance members navigating benefits and claims without routing through the call center.

90%Self-service rate
80%Call-center volume reduction
Read the case →

Industrial IoT Operator

Natural-language interface to IoT fleets

Natural-language layer over distributed IoT networks letting non-technical operators query and control devices without field-support visits.

75%Reduction in on-site support
Read the case →
/03

We meet your stack where it is

From Salesforce to Zalo, Kafka to QuickBooks: these are the systems we wire agents and pipelines into, and the platforms we build on.

CRM & customer support

Salesforce HubSpot Zendesk

Commerce & payments

Shopify Shopee Stripe Square QuickBooks

Messaging & social

WhatsApp Zalo Slack Microsoft Teams Twilio Instagram Facebook TikTok LinkedIn Google Maps TripAdvisor

Workspace & docs

Gmail Google Sheets Google Drive Google Calendar Notion Airtable Zoom Mailchimp

Data & infrastructure

PostgreSQL MongoDB Redis Elasticsearch Apache Kafka Grafana Kubernetes

AI models & platforms we build with

Claude OpenAI Gemini MCP AWS Azure Google Cloud Oracle Cloud Supabase Auth0 n8n Zapier Make

Pick your stack and watch the automation map draw itself.

Open the map
/04

How we work

Gates, not contracts

Discovery, build, pilot, production. Each phase ends in a go/no-go decision that you make with working software in front of you. Nobody signs a fixed-price twelve-month deal here.

Senior only, on staff

Every engineer on your project has 10+ years of experience and works for Lakeshore, not a subcontractor chain. You know who is writing your code, and they are in your standup.

Production is the product

Demos are easy; trust is hard. Everything we ship carries an evaluation harness, observability, and the dashboards your team needs to run it: accuracy, drift, latency, cost per query.

You own everything

Full IP assignment on all engagements. Code, prompts, evals, infrastructure: when we leave, your team can run it without us. We measure ourselves on that.

/05

Founder-led, with receipts

Lakeshore Labs is led by Ali Rathore, a founding engineer who builds enterprise agentic data platforms in production. Before Lakeshore: database core engineering at SAP HANA, autonomous robotics, a big-data platform acquired by Oracle, and engineering leadership across healthcare. He sets the architecture and standards on every engagement.

Matisse.ai dental shade matching

Computer-vision SaaS platform matching ceramic restoration colors to patient tooth shades, spanning iOS capture, ML color models, and a clinician web product, productized as Matisse.ai.

Read the case →

IoT fleet management for delivery trucks

In-truck telemetry and predictive analytics for a large Philippine delivery fleet: Raspberry Pi devices reading GPS and engine data over OBD-II, streaming into route and driver-behavior models that reduced fuel consumption and theft incidents.

Read the case →

Real-time transaction anomaly detection

Streaming anomaly detection over point-of-sale transactions for a US convenience-store chain, flagging fraudulent activity in real time with time-series models.

Read the case →

SparklineData SNAP analytics platform

Self-serve OLAP analytics on Apache Spark sustaining 10,000+ queries per second, with intelligent caching, query optimization, and a usage-based licensing model.

Read the case →

Founder track record, delivered with prior teams. Everything above was delivered by Lakeshore.

Tell us what you want to exist.

Two weeks and $15K later, you will be looking at it running against your data.

Book a 20-minute call hello@lakeshorelabs.ai